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An improved cluster labeling method for support vector clustering

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2 Author(s)
Jaewook Lee ; Dept. of Ind. Eng., Pohang Inst. of Sci. & Technol., South Korea ; Daewon Lee

The support vector clustering (SVC) algorithm is a recently emerged unsupervised learning method inspired by support vector machines. One key step involved in the SVC algorithm is the cluster assignment of each data point. A new cluster labeling method for SVC is developed based on some invariant topological properties of a trained kernel radius function. Benchmark results show that the proposed method outperforms previously reported labeling techniques.

Published in:

Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:27 ,  Issue: 3 )